MARC状态:审校 文献类型:西文图书 浏览次数:9
- 题名/责任者:
- Basic statistics for risk management in banks and financial institutions / Arindam Bandyopadhyay.
- 版本说明:
- First edition.
- 出版发行项:
- Oxford, United Kingdom : Oxford University Press, 2022.
- ISBN:
- 9780192849014:
- ISBN:
- 0192849018
- 载体形态项:
- xvii, 292 pages : illustrations ; 23 cm
- 个人责任者:
- Bandyopadhyay, Arindam, author.
- 论题主题:
- Banks and banking-Risk management.
- 论题主题:
- Risk management-Statistical methods.
- 中图法分类号:
- F830.22
- 书目附注:
- Includes bibliographical references and index.
- 内容附注:
- Introduction to risk management: basics of statistics -- Description of data and summary statistics for measurement of risk -- Probability and distribution theorems and their applications in risk management -- Hypotheses testing in baking risk analysis -- Matrix algebra and their application in risk prediction and risk monitoring -- Correlation theorem and portfolio management techniques -- Multivariate analysis to understand functional relationship and scenario building -- Monte Carlo simulation techniques and value at risk -- Statistical tools for model validation and back testing -- Time-series forecasting techniques for banking variables -- Appendix: statistical tables.
- 摘要附注:
- "The book provides an engaging account of theoretical, empirical, and practical aspects of various statistical methods in measuring risks of financial institutions, especially banks. In this book, the author demonstrates how banks can apply many simple but effective statistical techniques to analyze risks they face in business and safeguard themselves from potential vulnerability. It covers three primary areas of banking; risks-credit, market, and operational risk and in a uniquely intuitive, step-by-step manner the author provides hands-on details on the primary statistical tools that can be applied for financial risk measurement and management. The book lucidly introduces concepts of various well-known statistical methods such as correlations, regression, matrix approach, probability and distribution theorem, hypothesis testing, value at risk, and Monte Carlo simulation techniques and provides a hands-on estimation and interpretation of these tests in measuring risks of the financial institutions. The book strikes a fine balance between concepts and mathematics to tell a rich story of thoughtful use of statistical methods."--publisher.
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